Data Engineer (Mid-level)

WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working.

For more information, visit wppmedia.com.

Design, develop and maintain scalable ELT/ETL pipelines using modern cloud technologies.

Bachelor's Degree in Computer Science, Information Systems, Engineering, Data Science or a related quantitative discipline.
Google Cloud Professional Data Engineer certification (preferred).
Additional cloud or data engineering certifications are advantageous.
3–5 years' experience in Data Engineering or Analytics Engineering.
Experience developing cloud-based data platforms.
Experience building scalable data pipelines.
Experience integrating APIs and third-party platforms.
Experience working with modern data warehouses.
Experience supporting business intelligence and analytics platforms.
Experience within media, marketing technology or digital analytics is advantageous.
SQL (Advanced)
Python
REST APIs
JSON
Git
dbt
ETL / ELT
Data Modelling
Data Warehousing
Incremental Processing
Pipeline Orchestration
Data Quality Frameworks
Identity Resolution concepts
Google Cloud Platform
BigQuery
Cloud Storage
Cloud Functions
Cloud Run
Pub/Sub
Cloud Composer (Airflow)
IAM

Advantageous:
Snowflake
AWS
Azure
Terraform
Docker
Looker
Looker Studio
Power BI
Tableau
Google Analytics 4
Adobe Analytics (advantageous)

Experience integrating or working with data from:
Google Ads
Campaign Manager 360
DV360
Meta Ads
TikTok
AppsFlyer
SA360
Adverity
Modern Data Architecture
Cloud Computing
Data Governance
Data Privacy
Data Modelling
Data Quality
Data Observability
CI/CD Principles
Version Control
Cost Optimisation
Digital Marketing Ecosystem
AI-enabled Data Engineering

The successful candidate will:
Deliver reliable, scalable and secure data pipelines.
Maintain high levels of data quality and platform reliability.
Improve pipeline performance and reduce processing costs.
Enable trusted reporting through well-modelled datasets.
Deliver production-ready engineering solutions using best practices.
Contribute to continuous improvements in the data platform.
Produce clear technical documentation and reusable engineering assets.
Strong analytical thinking
Problem solving
Attention to detail
Curiosity and continuous learning
Ownership and accountability
Collaboration and communication
Adaptability
Innovation
Mentoring and knowledge sharing

The ideal candidate is passionate about building scalable cloud data platforms and solving complex data integration challenges. They have strong SQL and Python skills, experience working with modern cloud technologies, and enjoy developing reliable, maintainable data products that enable analytics across the organisation.
They are comfortable working with large-scale datasets, APIs, orchestration tools and cloud infrastructure, while collaborating with analysts, strategists and stakeholders to deliver high-quality data solutions. Experience within marketing technology, digital media or advertising ecosystems is advantageous but not essential.
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